{"provider_name":"Hatena Blog","author_name":"unifa_tech","author_url":"https://blog.hatena.ne.jp/unifa_tech/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Ftech.unifa-e.com%2Fentry%2F2019%2F08%2F08%2F090221\" title=\"Experimental method for Bio-Data augmentation using only two observations for deep learning applications.  - \u30e6\u30cb\u30d5\u30a1\u958b\u767a\u8005\u30d6\u30ed\u30b0\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","description":"By Matthew Millar R&D Scientist at \u30e6\u30cb\u30d5\u30a1This blog will show a new experimental method for data augmentation geared towards bio-science for deep learning. This is important for several reasons. 1: Collecting data is time-consuming especially in collecting large enough observations for training deep le\u2026","blog_url":"https://tech.unifa-e.com/","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/u/unifa_tech/20190805/20190805162245.png","type":"rich","version":"1.0","published":"2019-08-08 09:02:21","title":"Experimental method for Bio-Data augmentation using only two observations for deep learning applications. ","height":"190","blog_title":"\u30e6\u30cb\u30d5\u30a1\u958b\u767a\u8005\u30d6\u30ed\u30b0","provider_url":"https://hatena.blog","width":"100%","url":"https://tech.unifa-e.com/entry/2019/08/08/090221","categories":[]}